MACHINE LEARNING FOR CROP YIELD FORECASTING

Авторы: Бийбосунов Болотбек Ильясович , Бийбосунова Салтанат Кенешбековна

Тип документа: Статья

Год издания: 2023

Ключевые слова: YIELD, MODELING, FORECASTING, MACHINE LEARNING, CROPS, REGRESSION

Библиографическая ссылка:
https://www.elibrary.ru/item.asp?id=54925108
Аннотация

Amid the persistent rise in global population, there has been a heightened focus on food security by academia, governmental initiatives, and international endeavors. Food security serves as a critical pillar in the national security framework, contributing to a nation’s sovereignty and self-sufficiency in food supply. To fulfill global requirements for essential food items, there is an imperative need to enhance agricultural efficiency across countries. Concurrently, agricultural practices must align with contemporary quality standards and meet consumer needs, drawing upon an integrated approach to crop cultivation technologies and yield classifications. Methodologies and tools for yield augmentation, grounded in scientific advancements in predictive modeling, are of paramount importance. Investigating the plethora of variables that contribute to optimal crop development, which in turn influences yield, poses significant challenges. Comprehensive inquiries that incorporate cutting-edge scientific and technological methodologies are essential for creating precise yield forecasts...

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